PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Charting topographic maps based on UAV data using the image classification method

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A topographic map is a representation of the terrain, its landform and spatial elements present therein. Land surveying and photogrammetric measurements must be conducted in order to produce such cartographic document. The following must be done while obtaining information on topographic objects: determine the character and type of an object or phenomenon; determine the range of its occurrence; indicate a precise location. The next stage involves classification of objects into relevant classes and categories, i.e. arable land, pastures, forests, water basins, technical infrastructure, buildings, and other. Then, the determined classes undergo the process of cartographic generalization by combining smaller elements into a single complex, determination of a common border of their occurrence, and application of relevant graphic symbols and colours. The measuring technique which provides quick and accurate topographic information about the surrounding area is the one that uses Unmanned Aerial Vehicles (UAV). Digital photographs taken during the flight are the basis for generating a high-quality orthophotomap. Accurate determination of the location of individual spatial elements allows large-scale cartographic documents to be developed. This paper will present the method of charting topographic maps of rural areas based on orthophotomaps made from the photographs taken during the UAV flight. Supervised and unsupervised methods of object classification will be tested in order to increase the effectiveness of determination of types and occurrence range of individual topographic objects, and the obtained results will be used to chart a topographic map of the studied area.
Rocznik
Tom
Strony
77--85
Opis fizyczny
Bibliogr. 13 poz., rys.
Twórcy
  • Uniwersytet Rolniczy w Krakowie Katedra Geodezji 30-198 Kraków, ul. Balicka 253a
autor
  • Uniwersytet Rolniczy w Krakowie Katedra Geodezji Rolnej, Katastru i Fotogrametrii 30-198 Kraków, ul. Balicka 253a
  • Uniwersytet Rolniczy w Krakowie Katedra Geodezji Rolnej, Katastru i Fotogrametrii 30-198 Kraków, ul. Balicka 253a
Bibliografia
  • Abburu S., Golla S.B. 2015. Satellite Image Classification Methods and Techniques: A Review. International Journal of Computer Applications, 119, 8, 20–25.
  • Agüera-Vega F., Carvajal-Ramírez F., Martínez-Carricondo P. 2017. Assessment of photogrammetric mapping accuracy based on variation ground control points number using unmanned aerial vehicle. Measurement, 98, 221–227.
  • Awrangjeb M., Ravanbakhsh M., Fraser C.S. 2010. Automatic detection of residential buildings using LIDAR data and multispectral imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 65, 5, 457–467.
  • Cegielska K., Salata T., Gawroński K., Różyczka-Czas R. 2017. Level of Spatial Differentiation of Anthropogenic Impact in Małopolska. Journal of Ecological Engineering, 18, 18, 200–209.
  • Gonçalves J.A., Henriques R. 2015. UAV photogrammetry for topographic monitoring of coastal areas. ISPRS Journal of Photogrammetry and Remote Sensing, 104, 101–111.
  • Horning N. 2004. Land Cover Classification Methods. American Museum of Natural History. Centre for Biodiversity and Conservation, https://www.amnh.org/content/download/74344/ (accessed: 12.10.2017).
  • Höhle J. 2017. Generating Topographic Map Data from Classification Results. Remote Sensing, 9(224), 1–24.
  • Rusnák M., Sládek J., Kidová A., Lehotský M. 2018. Template for high-resolution river landscape mapping using UAV technology. Measurement: Journal of the International Measurement Confederation, 115, 139–151.
  • Santagata T. 2017. Monitoring of the Nirano Mud Volcanoes Regional Natural Reserve (North Italy) using Unmanned Aerial Vehicles and Terrestrial Laser Scanning. Journal of Imaging, 3(4), 1–10.
  • Smits P.C., Dellepiane S.G., Schowengerdt R.A. 1999. Quality assessment of image classification algorithms for land-cover mapping: A review and a proposal for a cost-based approach. International Journal of Remote Sensing, 20, 8, 1461–1468.
  • Ślusarski M., Siejka M. 2017. Model of quality of data collected in the topographic database. Proceedings of International Conference “17th International Multidisciplinary Scientific GeoConference SGEM2017”, 17, 23, 595–603.
  • Tong X., Liu X., Chen P., Liu S., Luan K., Li L., Hong Z. 2015. Integration of UAV-Based Photogrammetry and Terrestrial Laser Scanning for the Three-Dimensional Mapping and Monitoring of Open-Pit Mine Areas. Remote Sensing, 7, 6635–6662.
  • Turner I.L., Harley M.D., Drummond C.D. 2016. UAVs for coastal surveying. Coastal Engineering, 114, 19–24.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-014bb3a6-4ece-4e84-b88b-587b3a596cfe
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.